Unconventional hydrocarbon resources: geological statistics, petrophysical characterization, and field development strategies

T Muther, HA Qureshi, FI Syed, H Aziz, A Siyal… - Journal of Petroleum …, 2022 - Springer
Hydrocarbons exist in abundant quantity beneath the earth's surface. These hydrocarbons
are generally classified as conventional and unconventional hydrocarbons depending upon …

A review on application of data-driven models in hydrocarbon production forecast

C Cao, P Jia, L Cheng, Q Jin, S Qi - Journal of Petroleum Science and …, 2022 - Elsevier
The accurate estimation of production is the bottleneck technique that constraints the
efficient development of oil and gas fields. However, such multivariate and asymmetric …

Well production forecasting based on ARIMA-LSTM model considering manual operations

D Fan, H Sun, J Yao, K Zhang, X Yan, Z Sun - Energy, 2021 - Elsevier
Accurate and efficient prediction of well production is essential for extending a well's life
cycle and improving reservoir recovery. Traditional models require expensive computational …

Time-series production forecasting method based on the integration of Bidirectional Gated Recurrent Unit (Bi-GRU) network and Sparrow Search Algorithm (SSA)

X Li, X Ma, F Xiao, C Xiao, F Wang, S Zhang - Journal of Petroleum Science …, 2022 - Elsevier
With the gowning demand of improving quality and benefit of unconventional resources,
time-series production prediction plays an increasingly essential role in economic …

Well performance prediction based on Long Short-Term Memory (LSTM) neural network

R Huang, C Wei, B Wang, J Yang, X Xu, S Wu… - Journal of Petroleum …, 2022 - Elsevier
Fast and accurate prediction of well performance continues to play an increasingly important
role in development adjustment and optimization. It is now possible to predict performance …

Attention-based LSTM network-assisted time series forecasting models for petroleum production

I Kumar, BK Tripathi, A Singh - Engineering Applications of Artificial …, 2023 - Elsevier
Petroleum production forecasting is the process of predicting fluid production from the wells
using historical data. In contrast to the traditional methods of analysing surface and …

[HTML][HTML] Well production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm

CSW Ng, AJ Ghahfarokhi, MN Amar - Journal of Petroleum Science and …, 2022 - Elsevier
Developing a model that can accurately predict the hydrocarbon production by only
employing the conventional mathematical approaches can be very challenging. This is …

Estimated ultimate recovery prediction of fractured horizontal wells in tight oil reservoirs based on deep neural networks

S Luo, C Ding, H Cheng, B Zhang… - Advances in Geo …, 2022 - yandy-ager.com
Accurate estimated ultimate recovery prediction of fractured horizontal wells in tight
reservoirs is crucial to economic evaluation and oil field development plan formulation …

Machine learning based decline curve analysis for short-term oil production forecast

A Tadjer, A Hong, RB Bratvold - Energy Exploration & …, 2021 - journals.sagepub.com
Traditional decline curve analyses (DCAs), both deterministic and probabilistic, use specific
models to fit production data for production forecasting. Various decline curve models have …

Machine learning for deepwater drilling: Gas-kick-alarm Classification using pilot-scale rig data with combined surface-riser-downhole monitoring

Q Yin, J Yang, M Tyagi, X Zhou, X Hou, N Wang… - SPE Journal, 2021 - onepetro.org
Gas kicks occur frequently in deepwater drilling because of the extremely narrow mud-
weight window [minimum 0.01 specific gravity (sg)]. The traditional kick-detection method …